Thermal Error Analysis of CNC Machine Tool Feed System Based on SO-ELM
In order to predict the thermal error of CNC machine tool feed system more accurately,a numer-ical control machine tool feed system thermal error prediction model SO-ELM based on snake optimization(SO)algorithm and extreme learning machine(ELM)is proposed.Using fuzzy c-means clustering(FCM)and grey correlation analysis(GRA)to screen out key temperature measurement points of the feed system;Then,the snake optimization algorithm is used to optimize the input layer weights and hidden layer biases of the limit learning machine,and the SO-ELM thermal error prediction model is constructed using the temperature rise data and thermal error data of key temperature measurement points.To verify the accu-racy and applicability of the model,a comparative analysis was conducted with the thermal error prediction models based on SSA-BP and LSMT.The results showed that the root mean square error and determination coefficient of the SO-ELM model prediction results were better than those of SSA-BP and LSTM models,which can better predict the thermal error of the machine tool feed system and provide a new idea for the compensation of machine tool thermal error prediction.
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